Neural processing as causal inference

Highlights ► Neural circuits solve causal inference problems. ► Cortical circuits implement hierarchical predictive models. ► Neural variability reflects uncertainty about perceptual interpretations. ► This is a result of predictive coding in spiking neurons. ► Probabilistic inference accounts for a...

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Veröffentlicht in:	Current opinion in neurobiology 2011-10, Vol.21 (5), p.774-781
Hauptverfasser:	Lochmann, Timm, Deneve, Sophie
Format:	Artikel
Sprache:	eng
Schlagworte:	Action Potentials - physiology Cerebral Cortex - cytology Concept Formation - physiology Filters Humans Information processing Models, Neurological Nerve Net - physiology Nervous system Neural Networks (Computer) Neurology Perception Perception - physiology Probability Psychiatry Receptive field Reviews Sensation Sensory neurons Sensory Receptor Cells - physiology Synapses
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Beschreibung
Zusammenfassung:	Highlights ► Neural circuits solve causal inference problems. ► Cortical circuits implement hierarchical predictive models. ► Neural variability reflects uncertainty about perceptual interpretations. ► This is a result of predictive coding in spiking neurons. ► Probabilistic inference accounts for adaptive properties of sensory neurons.
ISSN:	0959-4388 1873-6882
DOI:	10.1016/j.conb.2011.05.018